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Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgment
  8. References
  9. Supporting Information

Primary Sjögren's syndrome (SS) is a systemic autoimmune inflammatory disease characterized by focal lymphocytic infiltrates in the lachrymal and salivary glands and autoantibodies against the SSA/Ro and SSB/La antigens. Experimental studies have shown an activation of NF-κB in primary SS. NF-κB activation results in inflammation and autoimmunity and is regulated by inhibitory and activating proteins. Genetic studies have shown an association between multiple autoimmune diseases and TNFAIP3 (A20) and TNIP1 (ABIN1), both repressors of NF-κB and of IKBKE (IKKε), which is an NF-κB activator. The aim of this study was to analyse single nucleotide polymorphisms (SNPs) in the IKBKE, NFKB1, TNIP1 and TNFAIP3 genes for association with primary SS. A total of 12 SNPs were genotyped in 1105 patients from Scandinavia (Sweden and Norway, = 684) and the UK (= 421) and 4460 controls (Scandinavia, = 1662, UK,= 2798). When patients were stratified for the presence of anti-SSA and/or anti-SSB antibodies (= 868), case–control meta-analysis found an association between antibody-positive primary SS and two SNPs in TNIP1 (= 3.4 × 10−5, OR = 1.33, 95%CI: 1.16–1.52 for rs3792783 and = 1.3 × 10−3, OR = 1.21, 95%CI: 1.08–1.36 for rs7708392). A TNIP1 risk haplotype was associated with antibody-positive primary SS (= 5.7 × 10−3, OR = 1.47, 95%CI: 1.12–1.92). There were no significant associations with IKBKE, NFKB1 or TNFAIP3 in the meta-analysis of the Scandinavian and UK cohorts. We conclude that polymorphisms in TNIP1 are associated with antibody-positive primary SS.


Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgment
  8. References
  9. Supporting Information

Primary Sjögren's syndrome (SS) is a systemic autoimmune inflammatory disease characterized by focal lymphocytic infiltrates in the lachrymal and salivary glands resulting in ocular and oral dryness. Extraglandular manifestations occur in about 30% of the patients, and autoantibodies against SSA/Ro and SSB/La are present in the sera of approximately 75% and 40% of the patients, respectively [1]. Patients with primary SS have a 16-fold increased risk of non-Hodgkin lymphoma, most commonly of the B cell type, and the presence of germinal centre formation in the lymphocytic infiltrates of the minor salivary glands has been suggested to predict lymphoma development [2, 3]. The class II histocompatibility leucocyte antigen (HLA) alleles HLA-DRB1*0301, DQA1*0501 and DQB1*0201 have been consistently associated with primary SS in Caucasians, in particular in patients positive for anti-SSA/SSB antibodies [4, 5]. Candidate gene studies of non-HLA genes have confirmed the association between primary SS and polymorphisms in the interferon regulatory factor 5 (IRF5) and signal transducer and activator of transcription 4 (STAT4) genes, while other reported candidate genes reviewed in Ice et al. await replication [6-9].

The A20 protein, encoded by tumour necrosis factor-alpha-induced protein 3 (TNFAIP3), is an ubiquitin-editing enzyme that serves as a negative regulator of tumour necrosis factor (TNF)- and Toll-like receptor (TLR)-stimulated activation of nuclear factor kappa B (NF-κB) [10]. The TNFAIP3 interacting protein 1 (TNIP1, alias A20-binding inhibitor of NF-κB, ABIN1), encoded by the TNIP1 gene, interacts with A20 in repressing the NF-κB activation [11]. In the cytoplasm, inhibitor of kappa B kinase epsilon, IKKε, encoded by the inhibitor of kappa light polypeptide gene enhancer in B cell kinase epsilon (IKBKE) gene, can activate NF-κB that translocate to the nucleus and subsequently activates pro-inflammatory and anti-apoptotic genes resulting in inflammation and cell survival [12]. NF-κB is a homo- or heterodimeric transcription factor where the p50–p65 heterodimer is the most common. The NFKB1 gene encodes the cytosolic non-DNA-binding p105 subunit, which is proteasome-processed to the active DNA-binding p50 subunit. TNIP1/ABIN1 has been shown to inhibit the processing of p105 to the p50 subunit, thereby reducing active p50–p65 [11].

Polymorphisms in TNFAIP3 and TNIP1 have been associated with several autoimmune diseases [13-22]. One study reported an association between TNFAIP3 and primary SS in patients of Caucasian origin, while a recent study did not replicate the finding in Han Chinese [15, 23]. In our previous study, a suggestive association between an NFKB1 single nucleotide polymorphism (SNP) and primary SS was found [24]. Polymorphisms in IKBKE associated with systemic lupus erythematosus (SLE), rheumatoid arthritis (RA) and antibody-positive primary SS have also been described [24-26].

The aim of this study was to investigate the association between the IKBKE, NFKB1, TNIP1 and TNFAIP3 genes in the NF-κB signalling pathway, with primary SS in patients from Scandinavia (in this study: Sweden and Norway) and the UK. In addition, the potential association with autoantibody status was investigated.

Materials and methods

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgment
  8. References
  9. Supporting Information

Patients and controls

In the discovery phase, 1699 samples (= 702 cases and = 997 controls) from Scandinavia (Sweden and Norway) were genotyped. Of these, 540 cases and 532 controls were included in our previous study [24]. After genotype quality control filters, removal of duplicate samples and non-Caucasian individuals, 1663 samples remained in the study. The final discovery cohort consisted of 684 cases (= 488 Swedish, = 196 Norwegian) and 979 controls (= 761 Swedish, = 218 Norwegian). All patients fulfilled the American European consensus criteria [27]. The controls were matched for age, gender and geographical area and consisted of healthy blood donors (= 709) and population-based controls (= 270) from the Malmö Cost-Cancer registry and the Epidemiological Investigation of Rheumatoid Arthritis (EIRA) control cohort [28]. The vast majority of the participants in the Malmö Cost-Cancer registry were Caucasians of Scandinavian origin, and in the EIRA control cohort, a genome-wide scan with Illumina Human Hap300 revealed a homogenous population with a low degree of population admixture [28]. In the replication phase, 683 healthy blood donor controls from Uppsala Bioresource, Sweden, were added to the Scandinavian cohort. Uppsala Bioresource is a permanent resource of genotyped healthy blood donors at the Uppsala Blood Transfusion Centre, Uppsala University Hospital, Sweden, that can be identified and used repeatedly as a source for DNA, RNA, sera and fresh peripheral blood mononuclear cells. The replication cohort from the UK consisted of 421 Caucasian patients with primary SS from the UK Primary Sjögren's Syndrome Registry (UKPSSR, www.sjogrensregistry.org) (Table S5) and 61 matched controls [29]. Genotype data for 2737 British healthy blood donor controls were obtained from the National Blood Donors (NBS) Cohort genotyped in the Wellcome Trust Case Control Consortium 2 (WTCCC2) project on the Illumina – Human1M-Duo BeadChip (www.wtccc.org.uk) [19]. Clinical data were obtained from the patient files (Table 1). All patients gave their informed consent, and the study was approved by the relevant ethics committees.

Table 1. Characteristics of Scandinavian and British patients with primary Sjögren's syndrome
 Scandinavia = 684UK = 421P-valuea
  1. n.s., not significant.

  2. a

    P-value for comparison between the Scandinavian and UK cohorts. Continuous variables compared with Mann–Whitney U-test and frequencies compared with χ2 test.

  3. b

    Data were not available from all patients.

Proportion of female patients92.8%94.1%n.s
Mean age ± SD (years)57.9 ± 13.559.8 ± 12.1n.s
Autoantibody frequency (%)b
Anti-SSA antibodies493/684 (72.1)357/418 (85.4)<0.0001
Anti-SSB antibodies301/680 (44.3)266/403 (66.0)<0.0001
Anti-SSA and/or anti-SSB antibodies505/684 (73.8)363/418 (86.8)<0.0001

Genotyping

In the discovery phase, 61 SNPs (IKBKE; n = 3, NFKB1; n = 1, TNIP1; n = 40 and TNFAIP3; n = 17) were genotyped (Table S1). The SNPs were selected because of their previous association with autoimmune diseases, and TNFAIP3 and TNIP1 were also covered with Tag-SNPs where r2 = 0.8 was considered as tagged. The following parameters were used for selecting the Tag-SNPs: (1) genotypes from the HapMap Caucasian (CEU) samples for SNPs with a minor allele frequency >0.001, (2) SNPs with an Illumina design score of >0.4 and (3) > 60 bp between SNPs. Genotyping was performed using 250 ng DNA extracted from peripheral blood samples of the study subjects, by the Illumina GoldenGate assay [30]. The genotype calls for A/T or C/G SNPs were reported following Illumina′s method for determining strand orientation (http://www.illumina.com/documents/products/technotes/technote_topbot.pdf).

Genotype quality control thresholds were SNP call rate > 90%, sample genotype call rate > 87%, minor allele frequency > 0.1% and Hardy–Weinberg (HW) equilibrium (> 0.001). Duplicate genotyping of 5.1% of the samples revealed one SNP in TNFAIP3 with duplicate failure, which was removed. After quality control filtering, 1663 samples of 1699 (97.9%) and 55 SNPs (IKBKE; n = 3, NFKB1; n = 1, TNIP1; n = 36; TNFAIP3; n = 15) of 61 (90.2%) remained for further analysis. For replication, 12 SNPs were selected based on the lowest P-values for each gene in the discovery phase and the SNP or a SNP proxy being available in the WTCCC2 data set. Genotyping was performed as mentioned above [30]. Sample call rate was 99.9% and SNP call rate 99.7%. Duplicate genotyping of 3.6% of the samples revealed no duplicate errors. In the WTCCC2 genotype data, the TNIP1 SNP rs10036748 (LD r2 = 0.86 with rs7708392) and the TNFAIP3 SNP rs2327832 (r2 = 0.95 with rs6920220) were available. Imputation for rs7708392 and rs6920220 was performed using IMPUTE2 with reference panel for sequence variants from the 1000 Genomes Phase I (build 37, release Mar 2012) [31]. We obtained information scores >0.93 for both SNPs. After imputation, only the imputed genotypes with a confidence score (probability) above 0.9 were retained for further analysis.

Statistical analysis

Allele frequencies in cases and controls were compared with χ2 allelic association test. The Cochran–Mantel–Haenszel test for meta-analysis of the Scandinavian and UK cohorts and the Breslow–Day test for heterogeneity of odds ratios between the cohorts were performed using plink software, version 1.07 (http://pngu.mgh.harvard.edu/~purcell/plink/) [32]. In the discovery phase where 61 SNPs were genotyped, a Bonferroni correction was performed (P = 0.05/61 = 8.2 × 10−4), and a nominal P of <8.2 × 10−4 was considered significant. In the replication phase, 12 SNPs were genotyped and the Bonferroni-corrected nominal P-value (0.05/12) of <4.2 × 10−3 was considered a significant association. Unadjusted p-values are presented. The Haploview, version 4.2, software (Broad Institute, Cambridge, MA, USA) was used to construct linkage disequilibrium (LD) plots between the SNPs in the 4460 controls.

Results

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgment
  8. References
  9. Supporting Information

Association with primary SS

In the discovery phase of our study, 55 polymorphisms in the IKBKE, NFKB1, TNIP1 and TNFAIP3 genes were genotyped and passed quality control, in 684 patients with primary SS and 979 controls from Scandinavia. In this analysis, we did not find any significant associations after correction for multiple analyses (Table S1). However, there were SNPs in each of the genes reaching a nominal P of ≤0.05, indicating that there might be significant associations with primary SS if a larger sample set was used. We therefore selected twelve SNPs that displayed low P-values in the discovery phase in each of the genes, and the TNIP1 SNP rs7708392 was selected for replication as it had shown an association with SLE in Swedish samples [22]. For replication, an independent cohort from the UK that consisted of 421 patients with primary SS and 2798 controls was included. Additional Scandinavian controls were included giving a total number of 684 primary SS cases and 1662 controls in the Scandinavian cohort. In this analysis, the TNFAIP3 SNP rs6920220 was found to be associated with primary SS in the Scandinavian cohort (nominal = 3.9 × 10−3, odds ratio (OR) = 1.24, 95%CI: 1.07–1.43), while there was no association with rs6920220 in the UK cohort or in the meta-analysis of the two cohorts. In the meta-analysis of the Scandinavian and UK cohorts, we detected significant association signals between primary SS and two SNPs in TNIP1: rs3792783 (nominal = 2.2 × 10−4, OR = 1.26, 95%CI: 1.12–1.43) and rs7708392 (nominal = 1.4 × 10−3, OR = 1.19, 95%CI: 1.09–1.32) (Table S2).

Association with antibody-positive primary SS

We also investigated the association between the 12 selected SNPs in patients with primary SS stratified according to presence of anti-SSA and/or anti-SSB antibodies in their sera. Among the Scandinavian patients 73.8% and among the UK patients 86.8% were positive for anti-SSA and/or anti-SSB antibodies (Table 1). Case–control analysis of patients with antibody-positive primary SS and the IKBKE, NFKB1, TNIP1 and TNFAIP3 polymorphisms detected a trend of more prominent association signal with TNIP1 compared with the case–control analysis that included all patients with primary SS. The TNIP1 SNPs rs3792783 and rs7708392 displayed significant signals of association with antibody-positive primary SS in the UK cohort alone. In the meta-analysis of the Scandinavian and UK cohorts, the association signal with the TNIP1 SNP rs3792783 was one order of magnitude (nominal = 3.4 × 10−5) higher, and the OR for association was increased to 1.33 (95%CI: 1.16–1.52) compared with 1.26 in the meta-analysis that included all patients with primary SS. The TNIP1 SNP rs7708392 was also significantly associated with antibody-positive primary SS (nominal = 1.3 × 10–3, OR = 1.21) in the meta-analysis of the Scandinavian and UK cohorts (Table 2 and Table S2).

Table 2. Association analysis of IKBKE, NFKB1, TNIP1 and TNFAIP3 with antibody-positive primary Sjögren's Syndrome in Scandinavian and UK cases and controls
GeneChrPolymorphismPositionaMinor allelebScandinaviaUKMeta-analysis
Minor allele frequencyP-valuecOR95% CIMinor allele frequencyP-valuecOR95% CIP-valuedOR95% CI
Ab pos Cases n = 505Controls n = 1662Ab pos Cases n = 363Controls n = 2798
  1. Chr, chromosome; Ab pos, antibody-positive (anti-SSA and/or anti-SSB positive); CI, confidence interval; OR, odds ratio.

  2. a

    Position build GRCh37.p5/hg19.

  3. b

    Minor allele based on the whole cohort of cases and controls.

  4. c

    Unadjusted P-value for differences in allele frequencies between antibody-positive patients and controls.

  5. d

    Combined P-value calculated using Cochran–Mantel–Haenszel χ2 test in a total of 868 antibody-positive cases and 4460 controls.

  6. e

    rs7708392 and rs6920220 were imputed in the WTCCC2 data. P-values and OR, 95% CI remaining significant after correction for the 12 SNPs tested are in bold.

IKBKE1rs17433930206652738G0.0630.092 3.6 × 10 −3 0.66 0.50–0.87 0.0730.0750.880.980.73–1.320.020.790.64–0.97
IKBKE1rs1539243206647786A0.140.189.0 × 1030.770.63–0.940.160.160.991.000.81–1.240.050.870.75–1.00
NFKB14rs4648022103496436A0.0740.0960.040.760.58–0.990.0740.0830.430.890.66–1.190.040.810.67–0.99
TNIP15rs3792783150455731G0.180.155.4 × 1031.301.08–1.570.200.16 2.0 × 10 −3 1.36 1.121.65 3.4 × 10 −5 1.33 1.161.52
TNIP15rs7708392e150457484C0.290.260.061.160.99–1.360.280.24 2.2 × 10 −3 1.27 1.071.51 1.3 × 10 −3 1.21 1.081.36
TNIP15rs12109187150448860C0.0450.0276.2 × 1031.661.15–2.380.0400.0330.351.210.81–1.808.6 × 1031.431.10–1.87
TNIP15rs2112635150432152G0.380.340.021.191.03–1.380.340.330.561.050.89–1.240.031.121.01–1.25
TNIP15rs871269150432387A0.280.320.040.850.73–0.990.310.320.660.960.81–1.140.070.900.80–1.01
TNFAIP36rs6920220e138006503A0.260.228.4 × 1031.241.06–1.460.230.220.451.080.89–1.290.011.171.03–1.32
TNFAIP36rs2230926138196065C0.0520.0370.031.441.04–2.000.0400.0350.541.130.76–1.680.041.301.01–1.68
TNFAIP36rs5029965138200851A0.0090.0130.270.670.33–1.380.0070.0150.090.470.19–1.160.050.570.33–1.00
TNFAIP36rs5029939138195722C0.0520.0370.031.441.04–2.000.0400.0370.681.090.73–1.620.061.280.99–1.65

The IKBKE SNP rs17433930 was found to be associated with antibody-positive primary SS in the Scandinavian cohort (nominal = 3.6 × 10−3, OR = 0.66). However, there was no signal of association with this SNP in the UK cohort or in the meta-analysis of the two cohorts. The NFKB1 SNP did not show any significant associations with antibody-positive primary SS in this analysis (Table 2). Finally, in the case-only association analysis of antibody-positive (= 868) patients against antibody-negative (= 234) patients, there were no associations with antibody status in either of the two cohorts or in the meta-analysis (Table S3). Tests for heterogeneity between the Scandinavian and UK cohorts did not detect any significant heterogeneity of OR between the cohorts for any of the analyses (Table S4).

Haplotype analysis

The two TNIP1 SNPs (rs3792783 and rs7708392), which showed a significant association with antibody-positive primary SS, are located in introns and in intermediate LD (r2 = 0.55), while the SNP rs12109187, which showed a near significant association, is in low LD with rs3792783 and rs7708392 (r2 <0.18) (Fig. 1A). A haplotype of the four TNIP1 SNPs that showed a nominal association of < 0.05 with antibody-positive primary SS in the meta-analysis was constructed using the combined genotype data from the Scandinavian and UK cohorts. This analysis defined a risk haplotype associated with antibody-positive primary SS with = 5.7 × 10−3, OR = 1.47 (95%CI 1.12–1.92), whereas the major alleles constituted a protective haplotype, = 2.8 × 10–3, OR = 0.86 (95%CI; 0.77–0.95) (Fig. 1B).

image

Figure 1. (A) TNIP1 haplotype diagram showing the five genotyped SNPs and their location on chromosome 5. The arrows indicate the SNPs associated with antibody-positive primary SS. Pairwise linkage disequilibrium (r2) plot between SNPs generated from the 4460 controls where black is r2 = 1, white is r2 = 0 (r2 × 100 is displayed). The TNIP1 gene is depicted with black boxes for exons, black lines for introns and orientation minus strand. (B) Haplotype frequencies in antibody-positive primary SS cases (n = 868) and controls (n = 4460) where the SNPs minor/major alleles included in the analysis are in order from left to right: rs2112635 (G/A), rs12109187 (C/A), rs3792783 (G/A), rs7708392 (C/G).

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Discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgment
  8. References
  9. Supporting Information

Here, we present for the first time the significant association between polymorphisms in TNIP1 and antibody-positive primary SS. The TNIP1 SNP rs3792783 that gave the highest signal of association in our study has also been associated with SLE and systemic sclerosis in Caucasians, with OR 1.26 and 1.47, respectively [20, 33]. The SNP rs7708392 has shown associations with SLE in multiple ethnicities with OR in the range of 1.27–1.40 [22, 33-36]. In primary SS, the HLA-DRB1*0301 risk allele in Caucasians is shared with patients with SLE and is particularly strongly associated with the presence of anti-SSA/SSB antibodies [37]. It is therefore not surprising that some genes associated with SLE will also be associated with primary SS, particularly in the subset of antibody-positive patients where the clinical features more often are systemic in nature. A pathogenic effect of anti-SSA antibodies in activating the NF-κB pathway has been demonstrated. Human salivary gland epithelial cells stimulated with anti-SSA antibodies from patients with primary SS or IgG from healthy individuals displayed increased NF-κB DNA binding and higher expression of pro-inflammatory genes when stimulated with anti-SSA antibodies [38].

The expression of TNIP1 mRNA and protein is reduced in skin biopsies from patients with systemic sclerosis compared with healthy controls. A study in SLE defined two risk haplotypes where the levels of TNIP1 mRNA and protein were decreased in EBV-transformed B cells from subjects carrying the risk haplotypes [20, 33]. Whether the altered TNIP1 expression affects the NF-κB activity in these situations has not been clarified. Conversely, an increased TNIP1 mRNA expression in psoriatic skin lesions has been reported [18]. A TNF-α-induced gene expression microarray in human cultured synoviocytes found an increase in TNIP1, TNFAIP3 and NFKB genes, and TNIP1 mRNA levels were higher in synovial biopsies from patients with RA compared with patients with osteoarthritis [39].

In this study, we did not find any associations with TNFAIP3 in the meta-analysis between the Scandinavian and UK cohorts at the Bonferroni-corrected significance level (< 4.2 × 10−3), either in the analysis of all patients with primary SS or in the analysis of patients with antibody-positive primary SS against controls. The SNP rs6920220, which was significantly associated with primary SS in the Scandinavian cohort when all patients were included (Table S2), is located 185 kb upstream of the TNFAIP3 promoter and conferrers risk for SLE, RA and type I diabetes [13, 17, 21]. The non-synonymous coding SNP rs2230926 in exon 3 of TNFAIP3 has been associated with multiple autoimmune diseases including primary SS and appears to be functional. The low frequency minor allele (Cys127) A20 protein is less effective than the major (Phe127), in inhibiting TNF-induced NF-κB activity [14, 15]. In this study, we did not find any significant associations with rs2230926.

We detected an association between the IKBKE SNP rs17433930 and antibody-positive primary SS in the Scandinavian cohort. The association was not replicated in the UK cohort and must therefore be interpreted with caution. This SNP is located in the tenth intron and has been associated with SLE in individuals of Swedish and European American origin, with similar minor allele frequencies and OR as for the Scandinavian cohort shown here [26]. Interestingly, a SNP in IKBKE, rs17433804 (r2 = 0.04 with rs17433930), was recently shown to be suggestively associated with patients with primary SS positive for germinal centre formations in their minor salivary gland biopsies [40]. The IKBKE-encoded IKKε is important in the antiviral response and activates both NF-κB and interferon regulatory factor 3 (IRF3) resulting in the production of proinflammatory cytokines [12]. The functional consequences of the SNP rs17433930 are unknown.

We were not able to replicate our previous association between the NFKB1 SNP rs4648022 and primary SS. There are to our knowledge, no reports of rs4648022 being associated with other autoimmune diseases but an association with non-Hodgkin lymphoma of different subtypes has been reported [41]. An NFKB1 promoter insertion/deletion (ins/del) polymorphism associated with colorectal cancer has been studied in rheumatic autoimmune diseases [42]. A meta-analysis found a possible association with certain autoimmune diseases in Asians but not in Caucasians, and a separate study did not detect any association with systemic sclerosis [43, 44]. In summary, studies hitherto have not shown any convincing associations between NFKB1 polymorphisms and rheumatic autoimmune diseases.

Approximately 5% of patients with primary SS will eventually develop lymphoma [2]. Somatic mutations in TNFAIP3 have been reported in lymphomas of several subtypes, most frequently of B cell origin, where mutations and/or deletions result in decreased protein expression and consequently increased NF-κB activation [45]. Less frequent somatic TNIP1 mutations in diffuse large B cell lymphomas have also been shown to affect its function as NF-κB suppressor [46]. Unfortunately, data on lymphoma development were not available from our patients. To study the association between polymorphisms in genes in the NF-κB signalling pathway and their functional consequences in primary SS patients with lymphoma will be interesting for the future.

Correcting for multiple testing is important in genetic studies, and we have applied Bonferroni correction for the number of SNPs tested. The Bonferroni adjustment is based on the assumption that all comparisons are independent. In a candidate gene study where genes are selected because of functions related to possible pathophysiological mechanisms and where SNPs in LD are correlated to some degree, a Bonferroni correction is too conservative and may result in type II errors [47]. We have therefore chosen to present uncorrected P-values for the reader to interpret.

Patients with primary SS positive for anti-SSA/SSB antibodies more often have extraglandular manifestations and express higher levels of cytokines in their sera compared with patients without such antibodies [1, 48]. There was a significant difference in the frequency of antibody-positive patients between the Scandinavian and UK cohorts. This might be due to different diagnostic inclusion criteria where the diagnosis relies more on positive anti-SSA/SSB antibodies than a positive minor salivary gland biopsy in the UK cohort, but different methods for measuring antibodies must also be taken into consideration [27]. Apart from the established HLA association with anti-SSA/SSB antibodies, an association between antibody-positive primary SS and NCR3, encoding the NK-cell-activating receptor NKp30, has been described [49]. In this study, we found a numerically strengthened association with TNIP1 when only antibody-positive patients were included. It is possible that patients with antibody-positive primary SS constitute a more homogenous group where the association with certain susceptibility genes is enhanced.

In conclusion, our study identified for the first time gene variants in TNIP1 associated with patients with antibody-positive primary SS. How these gene variants affect the NF-κB signalling pathway, disease development and clinical manifestations is an important topic for further studies.

Acknowledgment

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgment
  8. References
  9. Supporting Information

We thank Rezvan Kiani, Linda Öjkvist, Hawa Camara, Käth Nilsson, Lasse Gøransson, Erna Harboe and Marianne Eidsheim for collecting patient samples; Karolina Tandre at the Uppsala Bioresource and the Epidemiological Investigation of Rheumatoid Arthritis (EIRA) study for providing control samples; the Malmö Diet and Cancer Study/Malmö Preventive Medicine program for storing and providing DNA; Region Skånes kompetenscentrum för klinisk forskning (RSKC), Malmö for isolating DNA, the Wellcome Trust Case Control consortium (www.wtccc.org.uk) for access to genotype data; Gudlaug Kristjansdottir for selecting tag-SNPs; Jonas Carlsson Almlöf for handling the WTCCC2 data; the SNP&SEQ Technology Platform in Uppsala (www.genotyping.se) for genotyping; Sheryl Mitchell and Dennis Lendrem for coordinating data and sample collection; and Christine Downie for DNA isolation for the UKPSSR cohort. This work was supported by the Knut and Alice Wallenberg Foundation (A-CS), the Swedish Research Council for Medicine and Health (MWH, A-CS), the Swedish Rheumatism Association (GN, ET), the King Gustaf V 80-year Foundation (GN, MLE), the County Council of Östergötland and Linköping University Hospital (PE, CS), the Health and Medical Care Executive Board of the Västra Götaland (HFdE), the Medical Society of Göteborg and the Region Västra Götaland (HFdE), the Strategic Research Program at Helse Bergen, Western Norway Regional Health Authority (JGB, MVJ, RJ, RO, SJJ), the Broegelmann Foundation (JGB, MVJ, RJ) and the Medical Research Council UK (WFN, SB).

References

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgment
  8. References
  9. Supporting Information
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Supporting Information

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgment
  8. References
  9. Supporting Information
FilenameFormatSizeDescription
sji12101-sup-0001-TableS1-S5.docxWord document53K

Table S1. Discovery phase association analysis of IKBKE, NFKB1, TNIP1 and TNFAIP3 polymorphisms with primary Sjögren's syndrome in 684 Scandinavian cases (Sweden = 488, Norway = 196) and 979 controls (Sweden = 761, Norway = 218).

Table S2. Association analysis of IKBKE, NFKB1, TNIP1 and TNFAIP3 with primary Sjögren's Syndrome in Scandinavian and UK cases and controls.

Table S3. Association analysis of IKBKE, NFKB1, TNIP1 and TNFAIP3 in antibody-positive versus antibody-negative primary Sjögren's Syndrome cases.

Table S4. Heterogeneity of odds ratios between the Scandinavian and UK cohorts.

Table S5. UK Primary Sjögren's Syndrome Registry (UKPSSR) collaborators.

Please note: Wiley Blackwell is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.